To validate the association between body composition and mortality in men treated with radiation for localized prostate cancer (PCa). Secondarily, to integrate body composition as a factor to classify patients by risk of all-cause mortality.
Participants of NRG/Radiation Therapy Oncology Group (RTOG) 9406 and NRG/RTOG 0126 with archived computed tomography were included. Muscle mass and muscle density were estimated by measuring the area and attenuation of the psoas muscles on a single slice at L4-L5. Bone density was estimated by measuring the attenuation of the vertebral body at mid-L5. Survival analyses, including Cox proportional hazards models, assessed the relationship between body composition and mortality. Recursive partitioning analysis (RPA) was used to create a classification tree to classify participants by risk of death.
Data from 2066 men were included in this study. In the final multivariable model, psoas area, comorbidity score, baseline prostate serum antigen, and age were significantly associated with survival. The RPA yielded a classification tree with four prognostic groups determined by age, comorbidity, and psoas area. Notably, the classification among older (≥70 years) men into prognostic groups was determined by psoas area.
This study strongly supports that body composition is related to mortality in men with localized PCa. The inclusion of psoas area in the RPA classification tree suggests that body composition provides additive information to age and comorbidity status for mortality prediction, particularly among older men. More research is needed to determine the clinical impact of body composition on prognostic models in men with PCa.
Cancer. 2022 Dec 29 [Epub ahead of print]
Andrew M McDonald, Lyudmila DeMora, Eddy S Yang, John M Hoyle, Andrew Lenzie, Grant R Williams, Jeff M Michalski, Don Yee, Jean-Paul Bahary, Robert B Den, Mack Roach, Robert Dess, Mark V Mishra, Richard K Valicenti, Harold Y Lau, Samuel R Marcrom, Luis Souhami, Lucas C Mendez, Yuhchyau Chen, Desiree E Doncals, Stephanie L Pugh, Felix Y Feng, Howard M Sandler
Department of Radiation Oncology, University of Alabama at Birmingham O'Neal Comprehensive Cancer Center, Birmingham, Alabama, USA., Statistics and Data Management Department, NRG Oncology, Philadelphia, Pennsylvania, USA., School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA., Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, Alabama, USA., Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, USA., Radiation Oncology Department of Radiation Oncology, Edmonton Cross Cancer Institute, Edmonton, Alberta, Canada., Department of Radio Oncology, CHUM - Centre Hospitalier de l'Universite de Montreal, Montreal, Quebec, Canada., Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, USA., Department of Radiation Oncology, UCSF Medical Center-Mount Zion, San Francisco, California, USA., Department of Radiation Oncology, University of Michigan Comprehensive Cancer Center, Ann Arbor, Michigan, USA., Department of Radiation Oncology, University of Maryland/Greenebaum Cancer Center, Baltimore, Maryland, USA., Department of Radiation Oncology, University of California Davis, Sacramento, California, USA., Department of Oncology, Tom Baker Cancer Centre, Calgary, Alberta, Canada., The Research Institute, McGill University Health Centre (MUHC), Montreal, Quebec, Canada., Department of Oncology, London Regional Cancer Program, London, Ontario, Canada., Department of Radiation Oncology, University of Rochester, Rochester, New York, USA., Department of Radiation Oncology, Summa Health System - Akron Campus, Akron, Ohio, USA., Department of Radiation Oncology, UCSF Medical Center-Mission Bay, San Francisco, California, USA., Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California, USA.